Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects

The long-term effects of section transfers on return volatility: Intraday and overnight periods

Studies in Economics and Finance ◽

10.1108/sef-12-2020-0482 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Rodrigue Majoie Abo

Keyword(s):

Information Disclosure ◽

Fixed Effects ◽

Stock Return ◽

Control Variable ◽

Return Volatility ◽

Long Term Effects ◽

Macroeconomic Factors ◽

Content Type ◽

Stock Return Volatility

Purpose Studies on transfers to a more regulated section show an increase in information disclosure and stocks’ liquidity levels. Classical theories suggest that volatility should also be reduced. This study aims to analyse the long-term effects of a section transfer to a more regulated section (TSE 1/TSE 2) on stock return volatility. Design/methodology/approach This study uses an empirical framework relying on two-sample t-tests and panel regressions. These use robust standard errors and control for fixed effects, day effects and macroeconomic factors. The return variance of comparable stocks’ benchmark sample, instead of market variance, is used as a control variable. Comparable stocks operate within the same industry and do not transfer during the sample period. The authors test our results’ robustness using generalized autoregressive conditional heteroskedasticity estimates. Findings The study’s main findings show that pre-transferred stocks are more volatile than the stocks’ benchmark sample. The transfer to a more regulated section leads to a gradual decrease in the total daily stock return volatility, intraday return volatility and overnight return volatility. Originality/value To the best of my knowledge, this study is the first to empirically address the volatility change caused by the stocks’ transfer to a more regulated section. This study highlights the benefits of choosing section transfers to reduce volatility.

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Stock Return Volatility and Corporate Credit Risk

Journal of Derivatives and Quantitative Studies ◽

10.1108/jdqs-01-2012-b0001 ◽

2012 ◽

Vol 20 (1) ◽

pp. 1-40

Author(s):

Wan-Ho Jeong ◽

Chan-Pyo Kook

Keyword(s):

Credit Risk ◽

Stock Returns ◽

Stock Return ◽

Interval Data ◽

Return Volatility ◽

Short Term ◽

Market Data ◽

Stock Return Volatility ◽

Corporate Credit ◽

Term Data

In order to reinforce traditional credit indicators such as credit rate or financial ratio, many financial market data; such as the stock prices or their returns are used to evaluate corporate credit risk. Even though many structural models, which are using stock returns and their volatilities, are used to measure credit risk, empirical studies to find out how to measure desirable stock return volatility or which interval data is better for measuring the volatility are not enough. So, we tried to find out empirical evidences of following two questions. First, whether stock return volatility could be used as a timely indicator for credit events, such as bankruptcy or credit rate change. Second, which measure and which interval data are the best to calculate stock return volatility for credit indicator. We have reached the following empirical conclusions based on recent Korean stock market data. First, stock return volatility could be useful for early warning of credit events, because the volatility showed meaningful increase before the credit event. Second, 90~150 daily stock return data are useful to measure the volatility. Short-term data, less than 90 days are too sensitive to market circumstances and they easily increase without any credit level change. On the contrary, volatilities based on long-term data, more than 150 days are too smooth to use as a timely credit indicator. Third, in aspect of the measure of volatility, realized volatility which assume the averages of short-term stock returns are ‘zero’ is more efficient than traditional standard deviation. Those conclusions are based on recent Korean stock market data, so further robustness test should be followed.

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